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Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição deeplearning.ai

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35,373 classificações
3,714 avaliações

Sobre o curso

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Melhores avaliações

AM

Nov 23, 2017

I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

DC

Mar 08, 2018

Going beyond the technical details, this part of the course goes into the high level view on how to direct your efforts in a ML project. Really enjoyable and useful. Thanks for making this available!

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251 — 275 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Serhii K

Sep 21, 2017

This course give a lot of insights about approaching a machine learning problem. It doesn't contain a lot of concepts or algorithms regarding ML itself, but the course will be very helpful for anyone interested in working on real life ML systems.

por Shivam M

Feb 23, 2020

I think this course is one of the best course which teaches you how can you proceed your machine learning project in various situations and what measures to take while building a ML project. Hats off and thank you Andrew sir. Thank you coursera.

por Florian B

Sep 25, 2019

Very helpful to get an understanding of how to structure a machine learning project. Furthermore it is a great guide to get a first intuition on where to spend time or fix errors in a machine learning project and where to go on fast. Great work!

por Laure G

Aug 09, 2018

Ce cours donne des clés sur comment améliorer son réseau de neurones et en particulier éviter de perdre son temps à chercher dans la mauvaise direction.

Je n'ai pas encore mis en oeuvre cela, mais je pense que cela sera très utile le temps venu.

por Luam C T

Nov 02, 2017

It's an amazing course for people without ML experience overall. But if you have some experience (deep learning or not), you'll find a lot of basic tricks that you probably already used or figured out intuitively as you worked on some projects.

por Doipayan R

Nov 01, 2019

One of the most helpful 8 to 10 hours of instruction I have ever received in my life. Thanks a lot Andrew, and the entire team for putting this together. I will recommend this course to all my friends and colleagues working in the AI/ML space.

por Sayar B

Jul 30, 2018

Perhaps the most important course out of the 5 courses, Professor Ng explains really important concepts often overlooked by a lot of machine learning/ deep learning tutorials. This course will really make your good algorithms great.

Cheers! :)

por Gabriel S

Jul 11, 2018

the question on synthetic fog, I would love to know if someone answered to this one right from the first time. It is a designed trap to see if we are just listening to the class and applying or if we really think and work hard on each question

por Mahmoud H S

Jul 25, 2019

this is the greatest course I have ever seen in machine learning and deep learning. it gives students the best practice for applying machine learning in real projects and gain a lot of experience from one of the best machine learning experts.

por neeraj c

Apr 15, 2018

Practical tips distilled from years of hands-on experience delivered to be understood easily and intuitively. Will save a lot of time on getting started or getting accelerated on projects esp. for those with beginner or intermediate skills.

por Cyprien H

Nov 07, 2018

Very instructive course, full of practical and actionable advice to focus on the right problems in an ML project. The "flight simulators" are concrete examples of decisions one has to make in an ML project and it is good to practice with it.

por Jean D V

May 12, 2019

It does a great job of providing guidance on how you would plan a deep learning project. Transfer learning in particular is a very intriguing approach to leveraging previous work to speed up training a new neural network for your new task.

por Jeroen M

Jan 26, 2018

Material is excellent, Andrew is a brilliant teacher. Learned a lot. (Minor complaint: week 2's questions are formulated in a confusing way, making it hard to answer correctly even if you've understood the material of the course perfectly.)

por Deleted A

Nov 07, 2017

@Andrew Ng: Your statement "And I think that phonemes are an artifact created by human linguists. I actually think that phonemes are a fantasy of linguists." in: Whether to use end-to-end deep learning" Week 2, ROCKS !!!! GREAT and agree...

por Dr. M E J I

Sep 01, 2017

This is an excellent course for anyone in Deep Learning, Data Science, or Machine Learning. It is a little on the short side, but packed with good ideas about how to structure your projects when considering various differing data scenarios.

por Madagama G B S

Jan 25, 2020

This course helped me to systematically analyze errors in deep learning implementations. The machine learning flight simulator is a great way quickly learn how to address issues you would face in making practical machine learning problems.

por Fawad H

Nov 08, 2019

This Course is best for all level and it teaches in the best way to how to make your project to do well and how to suggest solution and how to detect problems in the training of the neural network. Thank you Andrew for making this course.

por Yingxiang Z

Jul 11, 2019

Very useful introduction to the real applied machine learning procedures. This course enables us to know exactly what steps to take in different phases of a project, and could potentially saves us a lot of time by avoiding useless efforts.

por Wong C H

Feb 18, 2018

"Experience can only be learnt by practicing" This course showed us some useful scenario which I think is very likely to be encountered in future projects. I think this will help to save time to develop deep learning model in the future.

por yugandhar n

Aug 29, 2017

Initially I thought It would be boring. But after taking the course, I feel the difference. Once again, Andrew Ng rocked it with composition of this course and quiz. I feel this is must course in deep learning, who is working in industry.

por Khaled J

May 20, 2019

Excellent class with practical advise to accelerate the application of best practices based on Andrew's experience. I would highly recommend this to practitioners wanting to save a lot of time learning these best practices the hard way.

por SUJITH V

Oct 28, 2018

Excellent course on understanding how and what to prioritise in ML projects. Not just helpful for people leading ML teams, but also for people who are doing some independent projects. ML is a lot of fun when you do experiments for fun :)

por Mohamed C S

Jul 19, 2018

Excellent Course, though it is an optional course, it is really worth taking it!

The Use case studies are just excellent! You can really have a taste of the problems encountered when you have to manage a deep learning project. Great work!

por Omid M

Jan 21, 2018

Great tips!

Minor issue: often the request for feedback for a lecture came right at the beginning of the lecture, covering big portion of the video ('was this video helpful'! ). It was annoying (I couldn't figure out how to minimize it).

por Takumi F

Dec 23, 2019

Highly recommended as it helps one think how to improve their ML models. Just do a 60/40 split and hoping for the best result is not the way to go, and this course definitely helps unveiling how to remove bias and variance from a model.